Millimeter-wave radars and laser radars are widely used in such fields as autonomous driving and advanced driver assistant system (ADAS). The laser radar can accurately sense the shape of an obstacle. The millimeter-wave radar can provide effective sensing data regarding the position and speed of the obstacle, and is not affected by rain and snow. In many examples of autonomous driving and ADAS, the position and attitude of the two types of sensors need to be calibrated to integrate data, so as to implement the accurate and robust detection of obstacles.
A calibration algorithm is used for calculating the conversion of coordinates between the millimeter-wave radar data coordinate system and the laser radar data coordinate system. Since the laser radar performs 3D obstacle measurement and the millimeter-wave radar performs 2D obstacle measurement, existing calibration methods cannot well solve the missing dimension of the millimeter-wave radar in terms of 3D measurement, affecting the accuracy of the calibration result. As a result, the laser radar and the millimeter-wave radar cannot be effectively used to implement the accurate detection of the positions of obstacles around a vehicle.